The latest Chinese drama I am watching is Our Interpreter. This isn’t a drama review but a personal musing on language, translation, and the growing companionship between AI and human interpreters. Some shows entertain, some distract, and a rare few slip into your thoughts and settle there. This one quietly made me pause.
While watching one of the episodes, I found myself drifting away from the plot and drawn instead to the small tug-of-war between an AI translator and a human interpreter. It was subtle, almost hidden in the scene, yet it sparked something in me. I told myself, “Vidya, take stock. You aren’t watching the story anymore; you’re debating the language in your mind.”
That was the beginning.
AI, Accuracy, and the Joy of Structure
Watching the AI do its job was impressive. Clean, sharp, consistent translations with no hesitation. It made me wonder if AI would have an immense amount of joy translating Indian languages. Each one is a treasure chest — emotional, layered, unpredictable.
AI translations don’t get moody. They don’t soften sentences because it “sounds better,” nor do they over-emphasise something out of cultural instinct. They stay obedient to the structure. Accuracy — that is the spine, the prime and penultimate goal.
There is a comfort in that predictability.
You know what you will get every time.
AI reminds me of semiya strands — thin, precise, obedient. No matter how many times you cook them, they remain the same width. But human beings? We are a mix of emotional excess and emotional reserve. Our language is a labyrinth we wander in and out of depending on the day, the weather, and how strong our morning chai was.
Sometimes I almost feel bad for AI. It learns one turn of phrase and then feels “cheated” when humans twist it into five meanings. Like a child whose parents keep changing the rules. Confusion is inevitable.
When the Human Interpreter Enters the Scene
And then came the human interpreter in Our Interpreter, pitted against an AI model in a translation competition. The moment she began to speak, the entire room shifted. The words were almost the same, but the delivery carried a depth no machine could mimic.
A small shift in tone.
A gentle softening.
A careful pause.
Suddenly the sentence felt warmer, more alive.
Humans pick up things without realising they are picking them up —
the hesitation behind a sentence,
the tension in someone’s shoulders,
the cultural sensitivity hidden between two words.
A machine can translate the sentence.
A human can translate the moment.
And the movement of a conversation.
How Language Actually Works in Real Life
The more I watched, the more I reflected on how language works outside the screen. We do not speak in neat, perfect lines. We speak in emotions, in pauses, in half-finished thoughts. In the quiet bravery of trying to say something difficult without hurting someone.
Literal translation cannot always hold the weight of lived experience.
Sometimes a word needs to bend slightly to protect someone’s dignity.
Sometimes a tone needs to curve to soften the impact.
Humans do this instinctively — the way we add lemon pickle to steaming semiya upma. Adjusting taste, reading the moment, not following a rulebook.
A Personal Anecdote: My Life with Translators
After receiving my PR card, a few months passed before I finally got a call for an interview as a Project Coordinator in a translation processing company. Little did I know that it would become one of the most enriching chapters of my life.
Suddenly, I found myself interacting daily with more South Asian languages than I had fingers to count. I wasn’t the translator — I was the mediator. I coordinated with translators, using English as the bridge.
And I loved it.
I felt super thrilled connecting with them through the beautifully structured Word files designed for error-free translation. Some languages used very few words, simple and neat. Others needed half a paragraph to express what English covered in eight letters. I enjoyed watching the personality of each language unfold through the translators’ choices.
Validation was its own small joy.
You learn more about people by reading their language than by reading their résumé.
Growing Up Multilingual (Even Without Speaking Everything)
I grew up listening to languages more than speaking them. I could understand several South Indian languages, Hindi, a little Urdu, and the regional languages that appeared every Sunday on television. Even if fluency danced just out of reach, I could always manage a greeting here or a phrase there.
Cinema was my earliest language teacher.
That’s why dramas today help me anchor subtle linguistic cues. They give a frame to the incredible diversity of the Indian demography. Each state has its uniqueness, its humour, its depth, and its unbeatable humaneness.
Recently, I learnt that Sanskrit is considered the paternal language in the architecture of many large language models. That thought gave me a small spark of joy. Imagine AI discovering cousinhood among languages — recognising patterns, connections, echoes of expressions across India’s linguistic map.
Even within Tamil, the language of my heart, the variations are endless. Madras Thamizh is its own glorious dialect — a delightful mix of English, improvised endings, and a swagger that only locals can fully deliver.
Take a simple phrase:
“Enna, epadi keera?”
Casually, it means: How are you?
But spoken with the right (or wrong!) inflection?
It becomes a challenge.
Almost a threat.
No AI system can decode that shift — not yet.
Learning Language by Watching Life
As a child, I never watched television passively. For me, every drama, every song, every spoken line was an opportunity to learn a language, notice a skill, or appreciate literature. I was observing, absorbing, and analysing all the moving parts of a scene — the music, the silences, the angles, the expressions.
Infotainment before the word existed.
I didn’t learn grammar.
I learnt people.
Chai, Strangers, and the Joy of Conversation
Every time I meet someone from another state, or another country, something opens inside me. I automatically become part of the “conversing committee.” I love exchanging linguistic nuances, learning about their world, and sharing bits of mine.
A cup of chai acts as the overture.
Warm. Inviting. Curious.
If the person is not from Tamil Nadu — or not from India — I become even more excited. These conversations expand my understanding and stretch my emotional quotient. Language becomes a bridge, not a boundary.
Why This Isn’t a Battle — It’s a Companionship
Many traditional translators may dismiss AI, especially in its early years, because we assume “being human” automatically makes us superior. We cast AI as a monster, a threat, or an unwanted shadow.
But I don’t see AI that way.
AI is not an endless prattle of “what I said, what you said, what they said.” It is a system trying to make sense of us — our contradictions, our tones, our cultural fingerprints.
What AI needs is gentleness.
Guidance.
A teacher’s patience.
Language Module Training is where the best of both worlds can meet — AI learning structure, humans offering emotional wisdom. It’s a partnership waiting to be refined.
A Chai-Table Realisation
Later, as I sat with my chai (which is usually when my thoughts decide to wander), a simple truth returned quietly:
Language doesn’t survive because we speak perfectly.
Language survives because we try to understand each other.
And one day, maybe, AI will be part of that effort too — not replacing us, but learning alongside us.
Machines may learn every word in every language someday.
But the pauses — those delicate hesitations where real meaning hides —
those still belong to us.
AI may know the words.
Humans will always know the pauses.
Itinerant Storyteller 